Human-machine interaction is necessary for the usage of a mobile terminal. A common way of human-machine interaction with a smart mobile terminal is to touch a screen of the mobile terminal through a finger, and the interaction is achieved via sensing touch pressure information of the finger by the sensor built in the mobile terminal. As Apple integrates the function of a voice assistant Siri to iPhone products, the way of human-machine interaction changes from conventional physical touch to voice control, i.e., to instruct the mobile terminal to accomplish a task desired by a user through human language. During the voice recognition, the user can casually give instructions in a natural language to voice assistant software, related devices of the mobile terminal receive the instructions, voice assistant software performs voice recognition and semantic analysis at a local and/or cloud server, and feeds back based on recognition and analysis results.
However, due to limitation of the conventional technology of voice recognition, especially of semantic analysis, accuracy is low in the recognition, error rates in recognition and analysis of multiple words, long sentences and multiple sentences are quite high, and the recognition and analysis results are usually far from a real desire of a user. The user needs to repeatedly input and keep revising the recognition and analysis results, which significantly affects the recognition accuracy and speed of the voice recognition method based on mobile terminal.